Pradeepkumar Bhale

About

Mr. Pradeepkumar Bhale received the Bachelor of Engineering in Computer Science and Engineering from the Govt. Collage of Engineering Aurangabad, Maharashtra, India, in 2010. Following that, he worked with Tech Mahindra Pvt. Ltd. as Technical Associate for a period of 2 years. Later on, he completed his Master of Technology in Information Security from ABV-Indian Institute of Information Technology Gwalior, Madhya Pradesh, India in 2014. He was awarded State of Maharashtra Post Graduate Fellowship for pursuing his Master. After that he joined as an Assistant Professor at Dr. B.R. Ambedkar National Institute of Technology Jalandhar, Punjab, India, and worked for 2 years. Currently, he is pursuing his Doctorate of Philosophy in the Department of Computer Science and Engineering, Indian Institute of Technology Guwahati, Assam under the supervision of Prof. Sukumar Nandi and Prof. Santosh Biswas. His current research interests are Internet-of-Things, wireless security, network security, and discrete event system modeling.

Profile link: https://scholar.google.com/citations?user=hHpL0uEAAAAJ&hl=en

Employment

• Dr BR Ambedkar National Institute of Technology Assistant Professor
  2014 - 2016
• Tech Mahindra Ltd Senior Software Engineer
  2010 - 2012

Education

• Indian Institute of Technology Guwahati Ph.d
  2016 - Present
• Atal Bihari Vajpayee Indian Institute of Information Technology and Management M.Tech
  2012 - 2014
• Government College Of Engineering Aurangabad Bachelor of Engineering
  2006 - 2010

Projects & Funding

Projects & funding information is unavailable.

Publications (23)

• A hybrid IDS for detection and mitigation of sinkhole attack in 6LoWPAN networks
  International Journal of Information Security 2024 DOI: 10.1007/S10207-023-00763-2
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• Effective injection of adversarial botnet attacks in IoT ecosystem using evolutionary computing
  Internet Technology Letters 2023 DOI: 10.1002/itl2.433
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• OPTIMIST: Lightweight and Transparent IDS With Optimum Placement Strategy to Mitigate Mixed-Rate DDoS Attacks in IoT Networks
  IEEE Internet of Things Journal 2023 DOI: 10.1109/JIOT.2023.3234530
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• A Novel Energy-Efficient Scheme for RPL Attacker Identification in IoT Networks Using Discrete Event Modeling
  IEEE Access 2023 DOI: 10.1109/ACCESS.2023.3296558
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• A Novel Approach to Detect Rank Attack in IoT Ecosystem
  International Conference on Innovations in Intelligent Computing and Communications 2022
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• DAISS: Design of an Attacker Identification Scheme in CoAP Request/Response Spoofing
  IEEE Region 10 Annual International Conference, Proceedings/TENCON 2021 DOI: 10.1109/TENCON54134.2021.9707405
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• LIENE: Lifetime Enhancement for 6LoWPAN Network Using Clustering Approach Use Case: Smart Agriculture
  Communications in Computer and Information Science 2021 DOI: 10.1007/978-3-030-75004-6_5
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• ML for IEEE 802.15. 4e/TSCH: Energy Efficient Approach to Detect DDoS Attack Using Machine Learning
  2021 International Wireless Communications and Mobile Computing, IWCMC 2021 2021 DOI: 10.1109/IWCMC51323.2021.9498637
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• ML for IEEE 802.15. 4e/TSCH: Energy Efficient Approach to Detect DDoS Attack Using Machine Learning
  International Wireless Communications and Mobile Computing Conference 2021
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• Energy efficient approach to detect sinkhole attack using roving IDS in 6LoWPAN network
  Communications in Computer and Information Science 2020 DOI: 10.1007/978-3-030-37484-6_11
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